How can derive new functional data structures from these techniques? Applications include just diverse areas as speeding up a variant of Haskell's venerable Data.Map, handling "big data" on disk without tuning for hardware, and parsing JSON faster in less memory.

How can derive new functional data structures from these techniques? Applications include just diverse areas as speeding up a variant of Haskell's venerable Data.Map, handling "big data" on disk without tuning for hardware, and parsing JSON faster in less memory.

Revision as of 13:07, 7 May 2014

Important:
ZuriHac has reached capacity. Registration is now closed. Thank you for your understanding.

Important:
Switzerland has its own power sockets. We can't provide converters for everybody so make sure to bring one along. Do note that the Europlug will fit in a Swiss power socket. There's an electronics shop Fust Center Eschenmoser very near our office where you can buy converters.

1 About

On the first weekend of June 2014 the Zurich HaskellerZ Meetup group will organize ZuriHac 2014, a three day Haskell Hackathon hosted at the Better offices. This is the third Haskell Hackathon in Zurich. The previous two were ZuriHac2013 and ZuriHac2010.

The Haskell Hackathon is an international, grassroots collaborative coding festival with a simple focus: build and improve Haskell libraries, tools, and infrastructure.

This is a great opportunity to meet your fellow haskellers in real life,
find new contributors for your project, improve existing libraries and tools or
even start new ones!

Note that this event is open to any experience level, from beginners to guru's. In fact, one of the goals is to bring beginners in contact with experts so that the former can get a quick start in the Haskell community.

8 Schedule

8.1 Friday

8.1.1 Introduction

Please come before 11:00. At 11:00 there will be projects introduction and discussion.

8.1.2 Talk by Edward Kmett

Title: Functionally Oblivious and Succinct

Abstract:
This talk provides a whirlwind tour of some new types of functional data structures and their applications.

Cache-oblivious algorithms let us perform optimally for all cache levels in your system at the same time by optimizing for one cache for which we don't know the parameters. While Okasaki's "Purely Functional Data Structures" taught us how to reason about asymptotic performance in a lazy language like Haskell, reasoning about cache-oblivious algorithms requires some new techniques.

How can derive new functional data structures from these techniques? Applications include just diverse areas as speeding up a variant of Haskell's venerable Data.Map, handling "big data" on disk without tuning for hardware, and parsing JSON faster in less memory.

8.1.3 Haskell Katas

8.2 Saturday

8.2.1 Talk by Simon Marlow

Title: The Haxl project at Facebook (update)

Abstract:
The Haxl project aims to build a DSL in Haskell to be used by engineers at Facebook to write rules that catch spam and malware. The key idea is to use an Applicative/Monad abstraction that makes the use of external data efficient and concise, by automatically taking advantage of concurrency and opportunities for batching remote data requests.

At ZuriHac in August 2013 I gave a talk about Haxl when we had just started. Some 10 months later I'd like to talk about the progress we've made in pushing Haxl towards production use. There will be a lot of details and anecdotes in this talk about our experiences in replacing a large production system with a Haskell-based solution.